Cognitive maps in rats and men.

Tolman, E. C.

doi:10.1037/h0061626

Cited by 5,256 publications

(3,139 citation statements)

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“…changing either T or R. Learning T can happen in the absence of any rewards (Gläscher et al, 2010). That animals are able to do this was shown very elegantly in the classical work of Tolman (1948): animals that were exposed to a maze (but without food rewards hidden in it) were later faster at learning a route to a food reward than those not preexposed to the maze (Bouton, 2006). However, the number of branches in a decision tree scales as w d where w is the width of one level, and d the length of the action sequence.…”

Section: Model-based Learningmentioning

confidence: 99%

The role of learning-related dopamine signals in addiction vulnerability

Huys

Tobler

Hasler

et al. 2014

Progress in Brain Research

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Psychostimulants such as methylphenidate (MPH) and antidepressants such as fluoxetine (FLX) are widely used in the treatment of various mental disorders or as cognitive enhancers. These medications are often combined, for example, to treat comorbid disorders. There is a considerable body of evidence from animal models indicating that individually these psychotropic medications can have detrimental effects on the brain and behavior, especially when given during sensitive periods of brain development. However, almost no studies investigate possible interactions between these drugs. This is surprising given that their combined neurochemical effects (enhanced dopamine and serotonin neurotransmission) mimic some effects of illicit drugs such as cocaine and amphetamine. Here, we summarize recent studies in juvenile rats on the molecular effects in the mid-and forebrain and associated behavioral changes, after such combination treatments. Our findings indicate that these combined MPH + FLX treatments can produce similar molecular changes as seen after cocaine exposure while inducing behavioral changes indicative of dysregulated mood and motivation, effects that often endure into adulthood. Tables: 2 References: 254 ABSTRACT Dopaminergic signals play a mathematically precise role in reward-related learning, and variations in dopaminergic signalling have been implicated in vulnerability to addiction. Here, we provide a detailed overview of the relationship between theoretical, mathematical and experimental accounts of phasic dopamine signalling, with implications for the role of learning-related dopamine signalling in addiction and related disorders. We describe the theoretical and behavioural characteristics of model-free learning based on errors in the prediction of reward, including step-by-step explanations of the underlying equations. We then use recent insights from an animal model that highlights individual variation in learning during a Pavlovian conditioning paradigm to describe overlapping aspects of incentive salience attribution and model-free learning. We argue that this provides a computationally coherent account of some features of addiction. CONTENTS

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Section: Model-based Learningmentioning

confidence: 99%

The role of learning-related dopamine signals in addiction vulnerability

Huys

Tobler

Hasler

et al. 2014

Progress in Brain Research

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“…The change in place cells to these non-spatial aspects would seem to belie this hypothesis. As pointed out by Nadel [142], this does not doom the fundamental hypothesis that rodent navigation abilities require the presence of a cognitive map representation somewhere in the brain [150,224], or that the hippocampus is critical to its formation and use. Interestingly, extrahippocampal cells that show spatial tuning seem to be less sensitive to environment or other factors than hippocampal cells [123,167,201,203], suggesting that they may form part of this extra-hippocampal map.…”

Section: The Multiple-map Hypothesismentioning

confidence: 99%

“…Is the cognitive map as hypothesized by Tolman [224] and O'Keefe and Nadel [150] really just a single intrinsic coordinate system represented in the hippocampus? I would argue that it is much more than this.…”

Section: The Multiple-map Hypothesismentioning

confidence: 99%

The hippocampal debate: are we asking the right questions?

Redish

2001

Behavioural Brain Research

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For years, the debate has been: 'Is the hippocampus the cognitive map?' or 'Is the hippocampus the core of memory?' These two hypotheses derived their original power from two key experiments-the cognitive map theory from the remarkable spatial correlates seen in recordings of hippocampal pyramidal cells and the memory theory from the profound amnesias seen in the patient H.M. Both of these key experiments have been reinterpreted over the years: hippocampal cells are correlated with much more than place and H.M. is missing much more than just his hippocampus. However, both theories are still debated today. The hippocampus clearly plays a role in both navigation and memory processing. The question that must be addressed is rather: 'What is the role played by the hippocampus in the navigation and memory systems?' By looking at the navigation system as a whole, one can identify the major role played by the hippocampus as correcting for accumulation errors that occur within idiothetic navigation systems. This is most clearly experimentally evident as reorientation when an animal is lost. Carrying this over to a more general process, this becomes a role of recalling a context, bridging a contextual gap, or, in other words, it becomes a form of recognition memory. I will review recent experimental data which seems to support this theory over the more general spatial or memory theories traditionally applied to hippocampus.

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“…Cognitive mapping, first proposed by Tolman, is the best known example of 63 an allocentric process and is described as a complex mental representation of 64 a familiar environment that can be used to influence spatial behaviour and 65 decision-making (Tolman 1948;O'Keefe & Nadel 1978). One of the key 66 features of such an allocentric process is that an individual is able to navigate 67 based on the spatial relationships between multiple landmarks, sensory 68 features and possible routes within a particular environment (Iaria et al 2009).…”

Section: Introduction 44mentioning

confidence: 99%

Place versus response learning in fish: a comparison between species

2015

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26Place learning is thought to be an adaptive and flexible facet of navigation. 27Due to the flexibility of this learning, it is thought to be more complex than the 28 simpler strategies such as learning a particular route or navigating through the 29 use of cues. Place learning is crucial in a familiar environment as it allows an 30 individual to successfully navigate to the same endpoint, regardless of where 31 in the environment the journey begins. Much of the research to date focusing 32 on different strategies employed for navigation has used human subjects or 33 other mammals such as rodents. In this series of experiments, the spatial 34 memory of four different species of fish (goldfish, killifish, zebrafish and 35Siamese fighting fish) was analysed using a plus maze set-up. Results 36 suggest that three of the species showed a significant preference for the 37 adoption of a place strategy during this task whereas zebrafish showed no 38 significant preference. Furthermore, zebrafish took significantly longer to learn 39 the task than the other species. Finally, results suggest that zebrafish took the 40 least amount of time (seconds) to complete trials both during training and 41 probe. 42

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Cognitive maps in rats and men.

Cited by 5,256 publications

References 0 publications

The role of learning-related dopamine signals in addiction vulnerability

The role of learning-related dopamine signals in addiction vulnerability

The hippocampal debate: are we asking the right questions?

Place versus response learning in fish: a comparison between species

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